Traditional SEO vs. AI SEO: SEO, AEO, GEO, AI Overviews, and LLMs Compared

Search has entered a new era. Ranking in the top results used to mean visibility, traffic, and predictable growth. But today, users often get their answers before they ever click a website. Google’s AI Overviews, ChatGPT, Perplexity, Claude, and Gemini are changing not just what people see, but how they search in the first place.

For businesses, this shift raises new questions: Is traditional SEO still relevant? What role do new approaches like Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO) play? And how do AI Overviews and large language models (LLMs) fit into the picture?

To answer these, we’ll look at each layer, starting with traditional SEO and moving through AEO, GEO, AI Overviews, and finally LLMs, to show how they connect and why all of them matter.

Traditional SEO: The Foundation

Search visibility still begins with the basics. Traditional SEO is what makes your site discoverable in the first place. It’s the practice of aligning your website with the way search engines crawl, index, and rank content so that users can actually find you.

At its core, traditional SEO rests on three areas:

• On-page optimization – making sure each page speaks clearly to both users and search engines. That includes keyword targeting, logical site structure, internal linking, and optimized metadata like titles and descriptions.
• Technical SEO – ensuring your website loads quickly, works on mobile, and is free of barriers that might block search engines. Clean code, crawlable pages, XML sitemaps, and structured data all fall into this category.
• Off-page SEO – building authority signals outside of your website. Backlinks, press mentions, social proof, and brand reputation help search engines decide whether your content can be trusted.

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For years, these elements alone determined success. If you ranked on the first page, especially in the top three positions, you could count on steady, reliable traffic. This is still true to an extent: a site with weak technical SEO or thin content will struggle to perform in any environment.

The strengths of traditional SEO are clear. It builds credibility, drives organic traffic without ongoing ad spend, and compounds over time. A piece of evergreen content written today can still rank and generate results years from now.

But the limitations are just as clear in 2025. The results page looks nothing like it did ten years ago. Ads, shopping carousels, maps, and most importantly, AI-generated summaries now crowd the top. Even when you hold the number one organic spot, you may sit below several layers of content that capture user attention first. On top of that, zero-click searches mean many people never leave the search results at all.

This doesn’t make traditional SEO irrelevant, far from it. It remains the foundation. Without strong technicals, well-structured content, and a track record of authority, your site won’t even be considered for inclusion in AI-generated answers. But it also isn’t enough on its own. To compete in today’s landscape, traditional SEO must be paired with newer strategies designed for the way search actually works now.

Answer Engine Optimization (AEO): Becoming the Quick Answer

Search isn’t always about long explanations. Many times, people simply want a direct fact: What is retinol? How many calories are in an avocado? When was Instagram launched? These kinds of questions don’t call for a full article; they call for a clear, concise answer. That’s exactly what Answer Engine Optimization (AEO) is designed for.

AEO is the practice of shaping your content so it can be extracted and used as the direct answer to a factual question.

Where traditional SEO tries to help you rank higher on a list of links, AEO aims to make your content the one that is the answer itself.

How AEO Works

To optimize for AEO, content needs to be:

• Concise and clear: definitions or explanations that can be understood in one or two sentences.
• Well-structured: headings, subheadings, or FAQ formats that help search engines identify the right section.
• Supported by schema: structured data markup that signals exactly what your content is about.

When these elements are in place, your content is more likely to be pulled into snippets, voice results, or other “zero-click” answers.

Why AEO Matters

Even if users don’t click through, your brand gains visibility by being presented as the trusted authority. In voice search, for example, the assistant typically pulls from a single source. If that’s you, your brand owns the moment completely.

It’s also a way to build topical authority. If your site consistently provides accurate, easy-to-understand answers, search engines begin to recognize it as a go-to source in your space.

Where AEO Falls Short

AEO isn’t designed to handle complex or multi-layered queries. If someone asks “best laptops under $1,000” or “how to build a skincare routine for dry skin,” they’re not looking for a one-line answer. They want context, comparisons, and recommendations. 

For those queries, short factual snippets aren’t enough, which is where Generative Engine Optimization comes in. A simple way to think about it is this: AEO makes you the brand with the quick answer. GEO makes you the brand inside the bigger story.

Generative Engine Optimization (GEO): Shaping the Full Response

Not every search is a quick question. Many are open-ended, asking for comparisons, recommendations, or a step-by-step explanation. Traditional SEO doesn’t account for this, and AEO isn’t designed to answer it either. That gap is where Generative Engine Optimization comes in.

GEO is about creating content that can serve as the raw material for AI systems when they generate longer, narrative-style answers. Instead of providing a single fact, these systems pull together context, pros and cons, and supporting details to build a comprehensive response.

How GEO Works

Generative engines — like Google’s AI Overviews or tools such as ChatGPT and Claude — need more than a definition. They rely on sources that demonstrate topical depth and authority. 

That means content optimized for GEO should:

• Explore topics thoroughly instead of stopping at the surface.
• Connect related ideas and entities in a way AI can easily map.
• Provide clear explanations, examples, and context that can be repurposed into a narrative.

When you publish this type of content, you’re answering a question and also providing a knowledge base that AI systems can lean on when constructing broader explanations.

Why GEO Matters

The benefit of GEO is influence. If your content is consistently included in generative responses, your brand becomes part of the conversation when users are weighing options, comparing products, or learning how to solve a problem. Instead of fighting for clicks on a results page, you’re helping shape the answer itself.

Where GEO Has Challenges

Unlike traditional SEO or AEO, GEO is harder to measure. You won’t find a clear “ranking position” for generative results, and visibility can shift based on how a question is phrased or which system is answering. But while it’s less predictable, the potential impact is significant.

Consider the query “best laptops under $1,000.” A single snippet isn’t enough here. Users want comparisons, features, and trade-offs. AI systems will build that response by drawing from multiple trusted sources. If your content covers the space comprehensively — with detail, authority, and clear context — your brand has a much higher chance of being included.

AI Overviews: Where AEO and GEO Converge

AI Overviews are Google’s clearest signal that search has fundamentally changed. Instead of showing a list of blue links at the top of the page, Google now generates a summary that pulls from multiple sources and places it before the organic results. For many users, this AI-generated overview is the answer.

What makes AI Overviews important is that they don’t rely solely on one type of content. They combine both AEO-style and GEO-style inputs, depending on the query.

• For straightforward factual searches, Google favors content optimized for AEO. A definition like “What is hyaluronic acid?” will trigger a crisp, fact-based summary at the top.
• For broader or more conversational searches, Google leans on GEO. A query like “best moisturizer for sensitive skin” often results in a generative overview that lists options, compares benefits, and cites multiple sources.

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That means AI Overview Optimization isn’t really a separate discipline. It’s the outcome of having a strong AEO and GEO strategy layered on top of a solid SEO foundation. If your site delivers both the quick facts and the in-depth guidance, you stand a far greater chance of being included in the AI-generated summary that most users see first.

The opportunity is huge. Appearing in an AI Overview puts your brand above the fold, often before ads and shopping results, and can position you as a trusted authority immediately. But it’s also a moving target. 

Google continues to refine how AI Overviews are triggered, how they’re displayed, and which sources they cite. This unpredictability means brands need to think holistically: optimizing not just for one feature, but for the overall ecosystem of how AI systems extract and use information.

In other words, AI Overviews are the real-world application of both AEO and GEO working together. They reward brands that are concise, authoritative, and comprehensive — all at once.

LLMs and RAG: Beyond Google

AI Overviews may be Google’s answer to changing search behavior, but discovery is no longer limited to Google. Large Language Models (LLMs) like ChatGPT, Claude, Gemini, and Perplexity are quickly becoming places where people go first for answers, product advice, or even purchase decisions.

What Are LLMs?

Large Language Models are advanced AI systems trained on enormous amounts of text. Their strength lies in understanding natural language and generating human-like responses. Unlike traditional search engines, which mainly return lists of links, LLMs can explain concepts, compare options, and provide recommendations conversationally. 

These systems don’t operate exactly like a search engine, but the principles of AEO and GEO still apply.

• ChatGPT, Claude, Gemini – These models excel at creating long-form, context-rich responses. When you ask them a question, they don’t provide a single snippet; they generate explanations, comparisons, and step-by-step narratives. In practice, this is GEO in action almost all the time. Brands with detailed, authoritative, semantically connected content are more likely to have their material surface in these kinds of outputs.
• Perplexity – Unlike other LLMs, Perplexity combines generative responses with direct citations. For fact-based queries, it often lifts snippets and references alongside the narrative, blending AEO and GEO principles in a way that feels closer to a “search plus answer” hybrid.

How RAG Fits In

A key piece of technology behind these models is Retrieval-Augmented Generation (RAG). Instead of relying only on what the model was trained on, RAG systems “retrieve” relevant information from external sources in real time and then generate an answer based on both the retrieved content and the model’s reasoning.

This makes the responses fresher, more accurate, and more grounded in specific sources. For brands, it means your content doesn’t just matter for search engines; it can also become part of the knowledge base that LLMs draw on to construct answers.

In other words, the same strategies that make you visible in AEO and GEO also make you more likely to appear in LLM outputs. Clear, trustworthy content is what retrieval systems are designed to find, and detailed, authoritative content is what generative models rely on to build useful responses.

Conclusion: Layered SEO for the AI Era

The path to visibility has never been more complex. Ranking on page one used to guarantee clicks. Today, users are just as likely to get their answers from an AI Overview at the top of the results page or from a large language model outside of Google altogether.

That’s why SEO can no longer be approached as a single tactic. It has to be built in layers:

• Traditional SEO ensures your site is discoverable and authoritative.
• AEO makes your brand the direct answer to quick, fact-based queries.
• GEO positions you within longer, generative explanations and comparisons.
• AI Overviews represent the convergence of AEO and GEO inside Google’s results.
• LLMs and RAG extend this ecosystem beyond Google, with AI systems retrieving and generating answers from trusted sources in real time.

The common thread across all of these is clear: search engines and AI systems favor content that is credible, well-structured, and comprehensive. The brands that master each layer won’t just rank higher, they’ll shape the very answers users see, whether in a snippet, a generative overview, or an AI-driven response.

The future of visibility belongs to businesses that stop chasing rankings and start becoming the answer itself. Contact our SEO team to discover how we can assist your brand.